Transition model for coronavirus management

Antoine Djogbenou; Christian Gourieroux; Joann Jasiak; Paul Rilstone; Maygol Bandehali

doi:10.1111/caje.12550

Transition model for coronavirus management

Antoine Djogbenou
, Christian Gourieroux
, Joann Jasiak
, Paul Rilstone
, Maygol Bandehali

York University
University of Toronto
Toulouse School of Economics
CREST

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

Résumé

This paper examines the individual records of patients treated for COVID-19 during the early phase of the pandemic in Ontario. We trace out daily transitions of patients through medical care of different intensity and address the right truncation in the database. We also examine the sojourn times and reveal duration dependence in the treatments for COVID-19. The transition model is used to estimate and forecast the counts of patients treated for COVID-19 in Ontario, while adjusting for the right truncation and right censoring in the sample. This research is based on the Public Health Ontario (PHO) data set from May 7, 2020.

langue originale	Anglais
Pages (de - à)	665-704
Nombre de pages	40
journal	Canadian Journal of Economics
Volume	55
Numéro de publication	S1
Les DOIs	https://doi.org/10.1111/caje.12550
état	Publié - 1 févr. 2022
Modification externe	Oui

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10.1111/caje.12550

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title = "Transition model for coronavirus management",

abstract = "This paper examines the individual records of patients treated for COVID-19 during the early phase of the pandemic in Ontario. We trace out daily transitions of patients through medical care of different intensity and address the right truncation in the database. We also examine the sojourn times and reveal duration dependence in the treatments for COVID-19. The transition model is used to estimate and forecast the counts of patients treated for COVID-19 in Ontario, while adjusting for the right truncation and right censoring in the sample. This research is based on the Public Health Ontario (PHO) data set from May 7, 2020.",

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AB - This paper examines the individual records of patients treated for COVID-19 during the early phase of the pandemic in Ontario. We trace out daily transitions of patients through medical care of different intensity and address the right truncation in the database. We also examine the sojourn times and reveal duration dependence in the treatments for COVID-19. The transition model is used to estimate and forecast the counts of patients treated for COVID-19 in Ontario, while adjusting for the right truncation and right censoring in the sample. This research is based on the Public Health Ontario (PHO) data set from May 7, 2020.

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Transition model for coronavirus management

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